This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Despite many great advances in our understanding of the fundamental biology of nicotinic acetylcholine receptors, challenges remain to develop new therapeutics. The work proposed in this collaborative project builds significantly on a strong collaboration (Henchman et al., 2003 a,b;Ivanov et al., 2007;Cheng et al., 2007;Wang et al., 2008), taking it in the direction of drug discovery for the treatment of a variety of human diseases. This is expected to enable a great increase in productivity, building on pioneering computational docking efforts of the Sine group in particular (Gao et al., 2003;Wang et al., 2003). Molecular dynamics simulations and accelerated molecular dynamics simulations will be further developed and applied to probe the internal motions of nicotinic acetylcholine receptors and homologous proteins. The results will be analyzed to deepen our understanding of the normal and pathological activity of these receptors. A key goal of this new phase of collaboration will be the use of the sampled conformations along with emerging NBCR workflow tools as targets for the docking of small molecules to suggest lead compounds for drug discovery. In particular, this collaboration focuses on how the discovery of new drugs for neurological and psychiatric diseases represents another important scientific driver and translational opportunity for the continued development of these computational tools and workflow. This collaboration will extend the development and application of our Relaxed Complex Schemes, implemented in new workflows with an increasing array of tools, for drug discovery to examine how selective binding of ligands might be achieved in the receptor ligand-binding domains. Our work will focus not only on homology models of the ligand-binding domains of human receptors, but also on the AChBPs.